Scott Farrar CLMA, University of Washington Uni cation...
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Feature Structures, Unification Scott Farrar CLMA, University of Washington far- [email protected] Some grammatical phenomena Linguistic features Feature structures Operations on feature structures Subsumption Unification Features in the NLTK Creating feature structures FeatStruct behavior Feature Structures, Unification Scott Farrar CLMA, University of Washington [email protected] February 3, 2010 1/45
Transcript of Scott Farrar CLMA, University of Washington Uni cation...
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Feature Structures, Unification
Scott FarrarCLMA, University of Washington
February 3, 2010
1/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Today’s lecture
1 Some grammatical phenomenaLinguistic features
2 Feature structures
3 Operations on feature structuresSubsumptionUnification
4 Features in the NLTKCreating feature structuresFeatStruct behavior
2/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Verb types
Consider the phrase structure rules in the PTB for verbs:
VP → VBZ NP...breaks the jar
VP → VBP NP...break the jar
VP → VBD NP...broke the jar
VP → VBN NP...broken the jar
We could capture the regularity by a rule like this:VP → VBx NPWhat exactly is ‘x’ representing?
3/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Verb types
Consider the phrase structure rules in the PTB for verbs:
VP → VBZ NP...breaks the jar
VP → VBP NP...break the jar
VP → VBD NP...broke the jar
VP → VBN NP...broken the jar
We could capture the regularity by a rule like this:VP → VBx NPWhat exactly is ‘x’ representing?
3/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Noun types
And for nouns:
NP → DT NN...the book
NP → DT NNS...the books
We could capture the regularity by a rule like this:NP → DT NNxWhat exactly is ‘x’ representing?
4/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Noun types
And for nouns:
NP → DT NN...the book
NP → DT NNS...the books
We could capture the regularity by a rule like this:NP → DT NNxWhat exactly is ‘x’ representing?
4/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subject-Verb Agreement
The parrot talks.
*The parrot talk.
They know Mary.
*They knows Mary.
We sing.
*We sings.
Furthermore agreement infomation is not captured intreebanks such as the PTB:S → NP VPThe NNx in the NP does not depend on the VBx in the VP.
5/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subject-Verb Agreement
The parrot talks.
*The parrot talk.
They know Mary.
*They knows Mary.
We sing.
*We sings.
Furthermore agreement infomation is not captured intreebanks such as the PTB:S → NP VPThe NNx in the NP does not depend on the VBx in the VP.
5/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subject-Verb Agreement
The parrot talks.
*The parrot talk.
They know Mary.
*They knows Mary.
We sing.
*We sings.
Furthermore agreement infomation is not captured intreebanks such as the PTB:S → NP VPThe NNx in the NP does not depend on the VBx in the VP.
5/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subject-Verb Agreement
The parrot talks.
*The parrot talk.
They know Mary.
*They knows Mary.
We sing.
*We sings.
Furthermore agreement infomation is not captured intreebanks such as the PTB:S → NP VPThe NNx in the NP does not depend on the VBx in the VP.
5/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subject-Verb Agreement
The parrot talks.
*The parrot talk.
They know Mary.
*They knows Mary.
We sing.
*We sings.
Furthermore agreement infomation is not captured intreebanks such as the PTB:S → NP VPThe NNx in the NP does not depend on the VBx in the VP.
5/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subject-Verb Agreement
The parrot talks.
*The parrot talk.
They know Mary.
*They knows Mary.
We sing.
*We sings.
Furthermore agreement infomation is not captured intreebanks such as the PTB:S → NP VPThe NNx in the NP does not depend on the VBx in the VP.
5/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subject-Verb Agreement
The parrot talks.
*The parrot talk.
They know Mary.
*They knows Mary.
We sing.
*We sings.
Furthermore agreement infomation is not captured intreebanks such as the PTB:S → NP VPThe NNx in the NP does not depend on the VBx in the VP.
5/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
linguistic feature: a property-like element that changes thegrammatical behavior of syntactic constituents; the elementsinto which linguistic units, such as words, can be brokendown. For a given sub-domain of grammar, there is arelevant feature:
person: I go, you go, he goes
number: he dances, they dance
case: he brings John, John brings him
tense: go, went, gone
modality: may, can,
honorifics (e.g., Japanese)
evidentiality (e.g., Shipibo)
noun class (e.g., Chinese)
6/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rd
number: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.
case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directional
tense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpast
modality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitative
honorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorific
evidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklore
noun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Features and values
Definition
Features are usually modeled as pairs of feature names andfeature values. A value refers to the language-specificphenomenon within the sub-domain:
person: 1st, 2nd, 3rdnumber: singular, plural, paucal, dual, trial, etc.case: accusative, ergative, locative, directionaltense: past, present, future, hodiernal past, hesternalpastmodality: conditional, subjunctive, abilitativehonorifics: plus honorific, minus honorificevidentiality: visual, auditory, hearsay, folklorenoun class: I, II, III, etc.
See http://grammaticalfeatures.net for a nice summary offeatures from a strictly linguistics perspective.
7/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Ontology of features
Whereas NPs, VPs, NNs, etc. are conceived of as categories(first-order “citizens”) in the grammar, features are moreproperty-like.
The VP has the feature value ‘past tense’
The verb is a ‘past tense’ verb
The noun has a case feature ‘absolutive’.
Just like, for example, an object like a car can have a colorproperty red.
8/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Ontology of features
Whereas NPs, VPs, NNs, etc. are conceived of as categories(first-order “citizens”) in the grammar, features are moreproperty-like.
The VP has the feature value ‘past tense’
The verb is a ‘past tense’ verb
The noun has a case feature ‘absolutive’.
Just like, for example, an object like a car can have a colorproperty red.
8/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Ontology of features
Whereas NPs, VPs, NNs, etc. are conceived of as categories(first-order “citizens”) in the grammar, features are moreproperty-like.
The VP has the feature value ‘past tense’
The verb is a ‘past tense’ verb
The noun has a case feature ‘absolutive’.
Just like, for example, an object like a car can have a colorproperty red.
8/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Bundles of feature (values)
Sometimes features are conceived of as the atomic units thatcompose more complex categories.
A noun is a feature bundle of semantic, morphological andphonological features: form ‘dog’
number singular
animacy animate
9/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Bundles of feature (values)
Sometimes features are conceived of as the atomic units thatcompose more complex categories.
A noun is a feature bundle of semantic, morphological andphonological features: form ‘dog’
number singular
animacy animate
9/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Today’s lecture
1 Some grammatical phenomenaLinguistic features
2 Feature structures
3 Operations on feature structuresSubsumptionUnification
4 Features in the NLTKCreating feature structuresFeatStruct behavior
10/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Feature structures
A feature structure is, informally speaking, a set of featurenames and values: feature1 value1
feature2 value2
feature3 value3
A feature structure is defined according to particulargrammatical traditions:
Functional Unification Grammar
Lexical Functional Grammar
Head-Driven Phrase Structure Grammar (Ling566)
11/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Typed feature structures: HPSG formal definition
Definition
A typed feature structure is defined on a finite set offeatures Feat and a type hierarchy 〈Type, v〉. It is a tuple〈Q, r , δ, θ〉 where:
Q is a finite set of nodes,
r ∈ Q (r is the root node)
θ : Q −→ Type is a partial typing function
δ : Q × Feat −→ Q is a partial feature value function
subject to the following conditions:
1 r isn’t a θ-descendant.
2 all members of Q except r are θ-descendants of r .
3 Some systems add an extra (no cycles) condition:there is no node n or path π such that δ(n, π) = n.
from Copestake (2000), Appendix.
12/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Typed feature structures: HPSG formal definition
Definition
A typed feature structure is defined on a finite set offeatures Feat and a type hierarchy 〈Type, v〉. It is a tuple〈Q, r , δ, θ〉 where:
Q is a finite set of nodes,
r ∈ Q (r is the root node)
θ : Q −→ Type is a partial typing function
δ : Q × Feat −→ Q is a partial feature value function
subject to the following conditions:
1 r isn’t a θ-descendant.
2 all members of Q except r are θ-descendants of r .
3 Some systems add an extra (no cycles) condition:there is no node n or path π such that δ(n, π) = n.
from Copestake (2000), Appendix.
12/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
More about feature values
atomic value: an unstructured value, one with only one part[tense past
person 2
]
complex value: a structured value, itself a feature structuretense past
agreement
[person 2
number singular
]
13/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
More about feature values
atomic value: an unstructured value, one with only one part[tense past
person 2
]
complex value: a structured value, itself a feature structuretense past
agreement
[person 2
number singular
]
13/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Graphs or matrices
Feature structures are a type of attribute-value matrix(AVM), a more generalized data structure used to representall kinds of information. Feature structures (and AVMs) canbe represented as graphs with nodes and arcs (cf. text bookfigures)
Nodes correspond to variable values and the paths tothe variable names.
Arcs represent the feature names.
A feature path is a list of features through a featurestructure leading to a particular value.
14/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Graphs or matrices
Feature structures are a type of attribute-value matrix(AVM), a more generalized data structure used to representall kinds of information. Feature structures (and AVMs) canbe represented as graphs with nodes and arcs (cf. text bookfigures)
Nodes correspond to variable values and the paths tothe variable names.
Arcs represent the feature names.
A feature path is a list of features through a featurestructure leading to a particular value.
14/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Feature path
tense past
agreement
[person 2
number singular
]Path:〈agreement number〉 = singular
15/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Feature path
tense past
agreement
[person 2
number singular
]Path:〈agreement number〉 = singular
15/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Feature path
tense past
agreement
[person 2
number singular
]Path:〈agreement number〉 = singular
15/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Feature path
tense past
agreement
[person 2
number singular
]Path:〈agreement number〉 = singular
15/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Reentrant structures
Definition
Reentrant structure: one in which the attribute has avalue that is another feature structure.
S[
head 1
]NP
[head
[agr 2
]]VP
[head 1
[agr 2
]]
A feature structure can be used to represent partialinformation.
16/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Reentrant structures
Definition
Reentrant structure: one in which the attribute has avalue that is another feature structure.
S[
head 1
]NP
[head
[agr 2
]]VP
[head 1
[agr 2
]]
A feature structure can be used to represent partialinformation.
16/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
More linguistic examples
Feature structure for a verb:cat VB
lex | GO |tense past
aspect progressive
form “was going”
Feature structure for a noun:
cat NN
lex | dog |number PL
form “dogs”
17/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Linguistic examples
Feature structure for a noun phrase (e.g., the boy):26666666666666666666664
cat NP
spec 1
26664cat DT
number SG
definite yes
form “the”
37775
head 2
26664cat NN
number SG
lex | boy |form “boy”
37775definite yes
number SG
37777777777777777777775
18/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Today’s lecture
1 Some grammatical phenomenaLinguistic features
2 Feature structures
3 Operations on feature structuresSubsumptionUnification
4 Features in the NLTKCreating feature structuresFeatStruct behavior
19/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
Definition
Subsumption is a relation that holds between featurestructures. A less specific (more abstract) feature structuresubsumes an equally or more specific one. The subsumptionsymbol is v.
[number PL
]
v
[number PL
person 3
]v
number PL
person 3
lex | dog |
20/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
Definition
Subsumption is a relation that holds between featurestructures. A less specific (more abstract) feature structuresubsumes an equally or more specific one. The subsumptionsymbol is v.
[number PL
]v
[number PL
person 3
]
v
number PL
person 3
lex | dog |
20/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
Definition
Subsumption is a relation that holds between featurestructures. A less specific (more abstract) feature structuresubsumes an equally or more specific one. The subsumptionsymbol is v.
[number PL
]v
[number PL
person 3
]v
number PL
person 3
lex | dog |
20/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
[number PL
person 3
]
? ¬ v
[number PL
][
number PL]
?
¬ v
[number SG
][ ]
?
v
[number SG
]
21/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
[number PL
person 3
]?
¬ v
[number PL
][
number PL]
?
¬ v
[number SG
][ ]
?
v
[number SG
]
21/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
[number PL
person 3
]
?
¬ v[
number PL]
[number PL
]?
¬ v
[number SG
][ ]
?
v
[number SG
]
21/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
[number PL
person 3
]
?
¬ v[
number PL]
[number PL
]?
¬ v
[number SG
][ ]
?
v
[number SG
]
21/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
[number PL
person 3
]
?
¬ v[
number PL]
[number PL
]
?
¬ v[
number SG]
[ ]?
v
[number SG
]
21/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
[number PL
person 3
]
?
¬ v[
number PL]
[number PL
]
?
¬ v[
number SG]
[ ]?
v
[number SG
]
21/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
[number PL
person 3
]
?
¬ v[
number PL]
[number PL
]
?
¬ v[
number SG]
[ ]
?
v[
number SG]
21/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Subsumption
Criteria for vF v G iff:
For every feature x in F , F (x) v G (x), where F (x)means “the value of the feature x of feature structureF ”.
For all paths p and q in F such that F (p) = F (q), it isalso the case that G (p) = G (q).
22/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
Definition
Unification is a binary operation over two featuresstructures f 1 and f 2, used for comparing or combininginformation.
Unification of f 1 and f 2 either returns a merged featurestructure with the information from both f 1 and f 2, or falseif f 1 and f 2 are incompatible. The unification operator isrepresented by: t.[
number PL]t
[person 2
]=
[number PL
person 2
]
23/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
Definition
Unification is a binary operation over two featuresstructures f 1 and f 2, used for comparing or combininginformation.
Unification of f 1 and f 2 either returns a merged featurestructure with the information from both f 1 and f 2, or falseif f 1 and f 2 are incompatible. The unification operator isrepresented by: t.
[number PL
]t
[person 2
]=
[number PL
person 2
]
23/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
Definition
Unification is a binary operation over two featuresstructures f 1 and f 2, used for comparing or combininginformation.
Unification of f 1 and f 2 either returns a merged featurestructure with the information from both f 1 and f 2, or falseif f 1 and f 2 are incompatible. The unification operator isrepresented by: t.[
number PL]t
[person 2
]
=
[number PL
person 2
]
23/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
Definition
Unification is a binary operation over two featuresstructures f 1 and f 2, used for comparing or combininginformation.
Unification of f 1 and f 2 either returns a merged featurestructure with the information from both f 1 and f 2, or falseif f 1 and f 2 are incompatible. The unification operator isrepresented by: t.[
number PL]t
[person 2
]=
[number PL
person 2
]
23/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
For comparing information in two feature structures,unification can be used. Are two feature structures thesame, or are they incompatible?[
number PL]t
[number PL
]=
[number PL
][
number PL]t
[number SG
]= False
Unification preserves and possibly adds information to theresulting feature structure. This property is called:monotonicity
24/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
For comparing information in two feature structures,unification can be used. Are two feature structures thesame, or are they incompatible?[
number PL]t
[number PL
]=
[number PL
]
[number PL
]t
[number SG
]= False
Unification preserves and possibly adds information to theresulting feature structure. This property is called:monotonicity
24/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
For comparing information in two feature structures,unification can be used. Are two feature structures thesame, or are they incompatible?[
number PL]t
[number PL
]=
[number PL
][
number PL]t
[number SG
]=
False
Unification preserves and possibly adds information to theresulting feature structure. This property is called:monotonicity
24/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
For comparing information in two feature structures,unification can be used. Are two feature structures thesame, or are they incompatible?[
number PL]t
[number PL
]=
[number PL
][
number PL]t
[number SG
]= False
Unification preserves and possibly adds information to theresulting feature structure. This property is called:monotonicity
24/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
For comparing information in two feature structures,unification can be used. Are two feature structures thesame, or are they incompatible?[
number PL]t
[number PL
]=
[number PL
][
number PL]t
[number SG
]= False
Unification preserves and possibly adds information to theresulting feature structure. This property is called:
monotonicity
24/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The unification operation
For comparing information in two feature structures,unification can be used. Are two feature structures thesame, or are they incompatible?[
number PL]t
[number PL
]=
[number PL
][
number PL]t
[number SG
]= False
Unification preserves and possibly adds information to theresulting feature structure. This property is called:monotonicity
24/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification of dissimilar structures
[agreement
[number PL
]]t
[number PL
]=
agreement[
number PL]
[number PL
]
25/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification of dissimilar structures
[agreement
[number PL
]]t
[number PL
]=agreement
[number PL
][
number PL]
25/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification: example
Grammar entry for a sentence26666666666666666666664
cat S
voice active
agent 1
"cat NP
number 4
#
process 2
"cat VB
number 4
#patient 3
hcat NP
ipattern
264subject 1
verb 2
object 3
375
37777777777777777777775
26/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification: example
Grammar entry for a noun phrase2666666666666666666664
cat NP
spec 1
264cat DT
number 3
definite 4
375head 2
"cat NN
number 3
#number 3
definite 4
pattern
"first 1
second 2
#
3777777777777777777775
27/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification: example
Lexical entries in AVM formcat DT
definite yes
number SG
form “the”
cat DT
definite yes
number PL
form “these”
28/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification: example
Unifying a noun phrase with a determiner2666666666666666666664
cat NP
spec 1
264cat DT
number 3
definite 4
375head 2
"cat NN
number 3
#number 3
definite 4
pattern
"first 1
second 2
#
3777777777777777777775
t
26664cat DT
definite yes
number PL
form “these”
37775
29/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification: example
Unifying the right part of a noun phrase with a determiner264cat DT
number 3
definite 4
375 t
26664cat DT
definite yes
number PL
form “these”
37775 =
26664cat DT
definite yes
number PL
form “these”
37775
30/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification: example
Unifying the right part of a noun phrase with a determiner264cat DT
number 3
definite 4
375 t
26664cat DT
definite yes
number PL
form “these”
37775 =
26664cat DT
definite yes
number PL
form “these”
37775
30/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification: example
Result of unification
cat NP
spec 1
cat DT
number PL
definite yes
form “these”
head 2
[cat NN
number PL
]number PL
definite yes
pattern
[first 1
second 2
]
31/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Today’s lecture
1 Some grammatical phenomenaLinguistic features
2 Feature structures
3 Operations on feature structuresSubsumptionUnification
4 Features in the NLTKCreating feature structuresFeatStruct behavior
32/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The main features module
The NLTK has a module for feature structures andaccompanying operations: nltk.featstruct
The basic feature structure nltk.featstruct.FeatStructis implemented as a mapping (dictionary) from features tovalues.
>>>from nltk.featstruct import FeatStruct
>>>fs1 = FeatStruct(number=‘singular’, person=3)
>>>print fs1
[ number = ‘singular’ ][ person = 3 ]
33/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
The main features module
>>>fs2 = FeatStruct(type=‘NP’, agr=fs1)
>>>print fs2
[ agr = [ number = ‘singular’ ] ][ [ person = 3 ] ][ ][ type = ’NP’ ]
34/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification in the NLTK
The NLTK has an implementation of unification withnltk.featstruct.FeatStruct.unify().
fs1
[ agr = [ number = ‘singular’ ] ]
[ [ person = 3 ] ]
[ ]
[ type = ’NP’ ]
fs2
[ agr = [ number = ?n ] ]
[ ]
[ subj = [ number = ?n ] ]
35/45
Feature Structures,Unification
Scott FarrarCLMA, Universityof Washington [email protected]
Some grammaticalphenomena
Linguistic features
Feature structures
Operations onfeature structures
Subsumption
Unification
Features in theNLTK
Creating featurestructures
FeatStruct behavior
Unification in the NLTK
>>>print fs2.unify(fs3)[ agr = [ number = ‘singular’ ] ][ [ person = 3 ] ][ ][ subj = [ number = ‘singular’ ] ][ ][ type = ‘NP’ ]
36/45
Creating feature structures: FeatStruct
fs1 = FeatStruct(agreement= \
FeatStruct(number=‘singular’, person=‘third’))
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
Use the FeatStruct constructor; note how quotes are used.
Creating feature structures: FeatStruct
fs1 = FeatStruct(agreement= \
FeatStruct(number=‘singular’, person=‘third’))
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
Use the FeatStruct constructor; note how quotes are used.
Creating feature structures: FeatStruct
fs1 = FeatStruct(agreement= \
FeatStruct(number=‘singular’, person=‘third’))
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
Use the FeatStruct constructor; note how quotes are used.
Creating feature structures, short-hand
fs1 = FeatStruct("[agreement = \
[number=‘singular’,person=‘third’]]")
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
The feature structure is parsed from the string. Values arequoted.
Creating feature structures, short-hand
fs1 = FeatStruct("[agreement = \
[number=‘singular’,person=‘third’]]")
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
The feature structure is parsed from the string. Values arequoted.
Creating feature structures, short-hand
fs1 = FeatStruct("[agreement = \
[number=‘singular’,person=‘third’]]")
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
The feature structure is parsed from the string. Values arequoted.
Creating feature structures, short-hand w/o valuequotes
fs1 = FeatStruct("[agreement = \
[number=singular,person=third]]")
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
Value quotes aren’t necessary.
Creating feature structures, short-hand w/o valuequotes
fs1 = FeatStruct("[agreement = \
[number=singular,person=third]]")
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
Value quotes aren’t necessary.
Creating feature structures, short-hand w/o valuequotes
fs1 = FeatStruct("[agreement = \
[number=singular,person=third]]")
[ agreement = [ number = ‘singular’ ] ]
[ [ person = ‘third’ ] ]
Value quotes aren’t necessary.
Using indices
fs = FeatStruct("[\
NAME=Lee, \
ADDRESS=(1)[NUMBER=74, STREET=‘rue Pascal’],\
SPOUSE=[NAME=Kim, ADDRESS->(1)],]")
[ ADDRESS = (1) [ NUMBER = 74 ] ]
[ [ STREET = ‘rue Pascal’ ] ]
[ ]
[ NAME = ’Lee’ ]
[ ]
[ SPOUSE = [ ADDRESS -> (1) ] ]
[ [ NAME = ‘Kim’ ] ]
The index is assigned a value, and then referenced.
Using indices
fs = FeatStruct("[\
NAME=Lee, \
ADDRESS=(1)[NUMBER=74, STREET=‘rue Pascal’],\
SPOUSE=[NAME=Kim, ADDRESS->(1)],]")
[ ADDRESS = (1) [ NUMBER = 74 ] ]
[ [ STREET = ‘rue Pascal’ ] ]
[ ]
[ NAME = ’Lee’ ]
[ ]
[ SPOUSE = [ ADDRESS -> (1) ] ]
[ [ NAME = ‘Kim’ ] ]
The index is assigned a value, and then referenced.
Using indices
fs = FeatStruct("[\
NAME=Lee, \
ADDRESS=(1)[NUMBER=74, STREET=‘rue Pascal’],\
SPOUSE=[NAME=Kim, ADDRESS->(1)],]")
[ ADDRESS = (1) [ NUMBER = 74 ] ]
[ [ STREET = ‘rue Pascal’ ] ]
[ ]
[ NAME = ’Lee’ ]
[ ]
[ SPOUSE = [ ADDRESS -> (1) ] ]
[ [ NAME = ‘Kim’ ] ]
The index is assigned a value, and then referenced.
Using indices: reference before assignment
fs = FeatStruct("[\
NAME=Lee, \
SPOUSE=[NAME=Kim, ADDRESS->(1)], \
ADDRESS=(1)[NUMBER=74, STREET=‘rue Pascal’]]")
ValueError: Error parsing feature structure
[NAME=Lee,
SPOUSE=[NAME=Kim, ADDRESS->(1)], ...
^ Expected bound identifier
Using indices: reference before assignment
fs = FeatStruct("[\
NAME=Lee, \
SPOUSE=[NAME=Kim, ADDRESS->(1)], \
ADDRESS=(1)[NUMBER=74, STREET=‘rue Pascal’]]")
ValueError: Error parsing feature structure
[NAME=Lee,
SPOUSE=[NAME=Kim, ADDRESS->(1)], ...
^ Expected bound identifier
Using variables
from nltk.sem.logic import Variable
fs10=FeatStruct("\
[NP=[head=[agreement=?n]], \
VP=[head=(1)[agreement=?n]]]")
[ NP = [ head = [ agreement = ?n ] ] ]
[ ]
[ VP = [ head = [ agreement = ?n ] ] ]
Using variables
from nltk.sem.logic import Variable
fs10=FeatStruct("\
[NP=[head=[agreement=?n]], \
VP=[head=(1)[agreement=?n]]]")
[ NP = [ head = [ agreement = ?n ] ] ]
[ ]
[ VP = [ head = [ agreement = ?n ] ] ]
Example from textbook
What does this feature structure represent?26666664S
hhead 1
iNP
»head
hagreement 2
i–VP
»head 1
hagreement 2
i–
37777775
S → NPVP〈 NP head agreement 〉 = 〈 VP head agreement 〉〈 S head 〉 = 〈 VP head 〉
Example from textbook
What does this feature structure represent?26666664S
hhead 1
iNP
»head
hagreement 2
i–VP
»head 1
hagreement 2
i–
37777775S → NPVP
〈 NP head agreement 〉 = 〈 VP head agreement 〉〈 S head 〉 = 〈 VP head 〉
Example from textbook
What does this feature structure represent?26666664S
hhead 1
iNP
»head
hagreement 2
i–VP
»head 1
hagreement 2
i–
37777775S → NPVP〈 NP head agreement 〉 = 〈 VP head agreement 〉
〈 S head 〉 = 〈 VP head 〉
Example from textbook
What does this feature structure represent?26666664S
hhead 1
iNP
»head
hagreement 2
i–VP
»head 1
hagreement 2
i–
37777775S → NPVP〈 NP head agreement 〉 = 〈 VP head agreement 〉〈 S head 〉 = 〈 VP head 〉
Need to combine variables and indices
fs3=FeatStruct("\
[NP=[head=[agreement=?n]], \
VP=[head=(1)[agreement=?n]], \
S=[head->(1)]]")
[ NP = [ head = [ agreement = ?n ] ] ]
[ ]
[ S = [ head = (1) [ agreement = ?n ] ] ]
[ ]
[ VP = [ head -> (1) ]
Need to combine variables and indices
fs3=FeatStruct("\
[NP=[head=[agreement=?n]], \
VP=[head=(1)[agreement=?n]], \
S=[head->(1)]]")
[ NP = [ head = [ agreement = ?n ] ] ]
[ ]
[ S = [ head = (1) [ agreement = ?n ] ] ]
[ ]
[ VP = [ head -> (1) ]
Unification in NLTK
[ VP = [ head = [ agreement = [ number = ‘singular’ ] ] ] ]
[ [ [ [ person = ‘third’ ] ] ] ]
[ NP = [ head = [ agreement = ?n ] ] ]
[ ]
[ S = [ head = (1) [ agreement = ?n ] ] ]
[ ]
[ VP = [ head -> (1) ] ]
[ NP = [ head = [ agreement = (1) [ number = ‘singular’ ] ] ] ]
[ [ [ [ person = ‘third’ ] ] ] ]
[ ]
[ S = [ head = (2) [ agreement -> (1) ] ] ]
[ ]
[ VP = [ head -> (2) ] ]
Printed version looks odd, but graph is intact.
Unification in NLTK
[ VP = [ head = [ agreement = [ number = ‘singular’ ] ] ] ]
[ [ [ [ person = ‘third’ ] ] ] ]
[ NP = [ head = [ agreement = ?n ] ] ]
[ ]
[ S = [ head = (1) [ agreement = ?n ] ] ]
[ ]
[ VP = [ head -> (1) ] ]
[ NP = [ head = [ agreement = (1) [ number = ‘singular’ ] ] ] ]
[ [ [ [ person = ‘third’ ] ] ] ]
[ ]
[ S = [ head = (2) [ agreement -> (1) ] ] ]
[ ]
[ VP = [ head -> (2) ] ]
Printed version looks odd, but graph is intact.
